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Pivotal Health is a technology platform helping healthcare providers navigate complex reimbursement landscapes and dispute underpaid claims through an AI-driven platform. The company combines software, data, and service to simplify reimbursement workflows, reduce administrative burden, and help providers recover entitled reimbursement.
You'll join as Staff Data Scientist, Decisioning, responsible for improving the systems that determine how Pivotal makes high-value decisions in core workflows. This is a production-focused role at the intersection of data science, experimentation, modeling, economics, and software engineering—not a research-only position.
Key responsibilities include: improving decisioning systems affecting pricing, offer behavior, and workflow routing; designing and running experiments to validate whether product, rules, prompt, or model changes improve performance; building models, heuristics, and optimization logic under operational constraints; translating business objectives into measurable decisioning systems with clear tradeoffs; productionizing new logic with engineers rather than stopping at notebooks; designing feedback loops connecting model behavior to business outcomes; and contributing to configurable rules systems that make decisioning easier to manage.
You'll use AI actively as a force multiplier in your own workflow and help the team adopt AI-native working practices. Success in the first 6–12 months means meaningful improvements to the offer engine, high-quality experiments clarifying which changes work, stronger feedback loops, better visibility into tradeoffs, and becoming a trusted owner of an important decisioning surface.
Ideal candidates have strong applied data science instincts combined with a desire to ship production work. You're comfortable moving between modeling, experimentation, analysis, and product/engineering collaboration. You reason clearly about metrics, tradeoffs, and second-order effects, and you're pragmatic about choosing the right level of sophistication. Experience in pricing, revenue optimization, marketplace systems, lending, credit, ad tech, or healthcare operations is especially valued, as is experience designing experiments in production, working with Python, and partnering tightly with engineers to productionize models and logic.
